SovaraBook Demo

A living Wikipedia that tells AIhow to navigate your company.

Sovara collects the knowledge your agents need
but only asks humans when it matters.

Learn how

Interacting with your Sovara agent

Your Agent
How many active customers do we have?
Is the definition of active customer still "someone who has made a purchase in the last 90 days"?
Yes.
We currently have 2582 active customers.
Type your message...

Evaluating and improving your Sovara agent

Spot mistakes.
Fix mistakes.
Repeat.

1
Monitor

Detect erroneous runs

2
Diagnose

Spot mistakes inside a run

3
Correct

Tell Sovara what should have happened instead

Monitor

After you give on some runs, Sovara checks for each new run if it's similar to a labeled run. Like this, your organization builds hive intelligence and knows what the agent can do and what it can't do.

Sovara monitor view showing run similarity against labeled runs.

Diagnose

Once a run is selected, Sovara's built-in Observability tools let you inspect every step of the agent run and quickly spot mistakes and under-specifications.

Sovara run drill-down showing where an issue happened.

Correct

Modern LLMs do not lack intelligence as much as context and domain knowledge. SovaraDB lets your organization create reusable domain knowledge snippets.

SovaraDB screen for correcting future agent behavior.

Case studies

Sovara learns company knowledge and can navigate messy data and siloed business processes.
Sovara agents remember mistakes and never make them again. This makes them accurate and reliable.

Messy data Text-to-SQL accuracy improvement graphic

Translating English questions to SQL

We collaborated with a large organization to enable Text-to-SQL translation for their database administrators. The database encodes years of tribal knowledge that a general-purpose AI system cannot infer from schema alone. For example, similarly named tables such as FCLT_HIST and FCLT_HIST_1 represent different concepts, and domain terms like “levels” and “floors” are not interchangeable. As a result, out-of-the-box AI tools such as Codex and Claude Code answered only ≤15% of queries correctly. After iterating with Sovara, their Text-to-SQL agent achieved 81.7%.

Try it yourself

Try out a demo version of Sovara by downloading the installer for your platform. For more information on how to set up Sovara for your agent, follow these instructions. Don't have an agent? No problem. You can get started with our demo agent.

Install the Sovara desktop app

The desktop app is fully local. All your data stays on the machine where Sovara is deployed.

macOS

For Apple Silicon Macs.

Windows

For Windows machines.

Linux

For Debian/Ubuntu and Fedora/Red Hat-based distributions.

Set up your agent

Use the Python or TypeScript SDK to set up your agent for Sovara. We support out-of-the-box integrations with major agentic frameworks and agents built in plain Python or TypeScript.

Python SDKTypeScript SDKClaude Agent SDKClaude CodeCodexGoogle ADKOpenAI Agents SDKCrewAILangChainPython SDKTypeScript SDKClaude Agent SDKClaude CodeCodexGoogle ADKOpenAI Agents SDKCrewAILangChain

Once you have installed the desktop app, install the CLI tool and skill to use Sovara from your coding tool of choice.